Chapter 9: Buildings
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9.5 Non-technological and Behavioural Mitigation Options and Strategies
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9.5.1 Non-technological Determinants of Energy Demand and Carbon Emissions
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9.5.1.3 Socio-demographic Factors
Income is positively correlated to energy demand (Cayla et al. 2011; Sreekanth et al. 2011; Couture et al. 2012; Moura et al. 2015; Singh et al. 2017; Yu 2017; Bissiri et al. 2019; Mata et al. 2021b). High-income households tend to use more efficient appliances and are likely to be more educated and environmentally sensitive, but their higher living standards require more energy (Harold et al. 2015; Hidalgo et al. 2018). Low-income households are in higher risk of fuel poverty (Section 9.8).
Mixed effects are found for household size, age, gender, ethnicity, education levels and tenancy status (Engvall et al. 2014; Hansen 2016; Lévy and Belaïd 2018; Arawomo 2019; Rafiee et al. 2019). Single-parent and elderly households consume more gas and electricity, and gender has no significant effect (Brounen et al. 2012; Harold et al. 2015; Huang 2015). Similarly, larger families use less electricity per capita (Bedir et al. 2013; Kavousian et al. 2013). Heating expenditure tends to be higher for owners than for renters, despite the formers tendency to have more efficient appliances (Gillingham et al. 2012; Davis, 2012; Kavousian et al. 2015).
9.5.3 Adoption of Climate Mitigation Solutions – Reasons and Willingness
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Table 9.3 | Reasons for Adoption of Climate Mitigation Solutions. The sign represents if the effect is positive (+) or negative (–), and the number of signs represents confidence level (++, many references; +, few references) (Mata et al. 2021a).
Please refer to page 999 of the report to see Table 9.3, which references gender as a social-demographic factor.
9.8 Links to Sustainable Development
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9.8.4 Social Wellbeing
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9.8.4.2 Improved Access to Energy Sources, Gender Equality and Time Saving
In most low- and middle-income developing countries women and children (particularly girls) spend a significant amount of their time for gathering fuels for cooking and heating (World Health Organization 2016; Rosenthal et al. 2018). For example, in Africa more than 70% of the children living in households that primarily cook with polluting fuels spend at least 15 hours and, in some countries, more than 30 hours per week in collecting wood or water, facing significant safety risks and constraints on their available time for education and rest (World Health Organization 2016; Mehetre et al. 2017). Also, in several developing countries (e.g., in most African countries but also in India, in rural areas in Latin America and elsewhere) women spend several hours to collect fuel wood and cook, thus limiting their potential for productive activities for income generation or rest (García-Frapolli et al. 2010; World Health Organization 2016; Mehetre et al. 2017). Expanding access to clean household energy for cooking, heating and lighting will largely help alleviate these burdens (Malla et al. 2011; World Health Organization 2016; Lewis et al. 2017; Rosenthal et al. 2018). Jeuland et al. (2018) found that the time savings associated with the adoption of cleaner and more fuelefficient stoves by low-income households in developing countries are amount to USD1.3–1.9 per household per month, constituting the 23–43% of the total social benefits attributed to the promotion of clean stoves.
Electrification of remote rural areas and other regions that do not have access to electricity enables people living in poor developing countries to read, socialise, and be more productive during the evening, while it is also associated with greater school attendance by children (Torero 2015; Rao et al. 2016; Barnes and Samad 2018). Chakravorty et al. (2014) found that a grid connection can increase non-agricultural incomes of rural households in India from 9% up to 28.6% (assuming a higher quality of electricity). On the other hand, some studies clearly show that electricity consumption for connected households is extremely low, with limited penetration of electrical appliances (Cameron et al. 2016; Lee et al. 2017) and low quality of electricity (Chakravorty et al. 2014). The implementation of appropriate policies to overcome bureaucratic red tape, low reliability, and credit constraints, is necessary for maximising the social benefits of electrification.
